The dimensionality reduction space-time adaptive processing (STAP) can effectively suppress clutter and jamming in both spatial and temporal dimensions simultaneously. The discrepancy between training data and detection data can make the performance of STAP degrade, we propose interrupted sampling repeater jamming( ISRJ) to counter the joint-domain localized space-time adaptive processing (JDL-STAP). Firstly, the theory of JDL-STAP model is presented. By analyzing the feasibility of ISRJ model, we find that ISRJ can generate numerous false targets with different distributions between sampling data and detection data by changing the retransmitted parameters. And these false targets can destroy the independent identical distribution (IID) of system sample data seriously. Both simulated and measured results corroborate the effectiveness of the ISRJ methods against JDL-STAP.
Combining support vector machine with infrared spectrum analysis, the infrared spectra analysis model of mixed gas is established. Taken the mixed gas containing hydrocarbon as an example, the selection and optimization of model parameters is researched through experiment. Beginning with the SVM analysis model, infrared spectrometer and spectra data, spectra analysis band and spectrometer scanning interval, the detailed study of how the parameters like the types of kernel function for the SVM analysis model, penalty factor C, method of spectra data preprocessing, spectrometer scanning interval, spectra analysis band, etc. Affect the analysis result are carried out. The experimental results show that under the condition of the SVM analysis model is determined, a reasonable selection and optimization of the SVM analysis model parameter can improve the accuracy of the analysis results, and it has a practical application value.
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